Digital Implementation of Switching Model-Based Inductance Identification for IPMSM under Sensorless Control

Rotor position error is a critical factor affecting parameter identification accuracy. This paper proposes a rotor-position-free inductance identification method for Interior Permanent Magnet Synchronous Motors(IPMSMs) under sensorless control, utilizing a switching model-based digital implementation. In the conventional α-β frame IPMSM model, the switching effects of pulse-width modulation (PWM) inverters are neglected, where electrical parameters are assumed constant during steady-state operation and harmonic information is disregarded. To address these limitations, a switching-enhanced IPMSM model is established to explicitly incorporate PWM switching dynamics into the parameter identification process. By deploying a digital signal processor(DSP) to sample phase current ripples, the α-β axis current derivatives under both zero-voltage vectors and active voltage vectors are analytically computed, enabling position-independent inductance identification. Compared with existing sensorless methods, the proposed approach eliminates the need for signal injection, additional sensors, or operational disturbances while maintaining system simplicity. Experimental validation on a dSPACE hardware-in-the-loop(HIL) platform confirms the feasibility and effectiveness of the digital implementation for sensorless inductance identification.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/icesep66633.2025.11155598
Primary Topic
Electric Motor Design and Analysis
Type
article
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article

Digital Implementation of Switching Model-Based Inductance Identification for IPMSM under Sensorless Control

Fan Zhang
Electric Motor Design and Analysis
article

Digital Implementation of Switching Model-Based Inductance Identification for IPMSM under Sensorless Control

Fan Zhang
article en

Abstract

Rotor position error is a critical factor affecting parameter identification accuracy. This paper proposes a rotor-position-free inductance identification method for Interior Permanent Magnet Synchronous Motors(IPMSMs) under sensorless control, utilizing a switching model-based digital implementation. In the conventional α-β frame IPMSM model, the switching effects of pulse-width modulation (PWM) inverters are neglected, where electrical parameters are assumed constant during steady-state operation and harmonic information is disregarded. To address these limitations, a switching-enhanced IPMSM model is established to explicitly incorporate PWM switching dynamics into the parameter identification process. By deploying a digital signal processor(DSP) to sample phase current ripples, the α-β axis current derivatives under both zero-voltage vectors and active voltage vectors are analytically computed, enabling position-independent inductance identification. Compared with existing sensorless methods, the proposed approach eliminates the need for signal injection, additional sensors, or operational disturbances while maintaining system simplicity. Experimental validation on a dSPACE hardware-in-the-loop(HIL) platform confirms the feasibility and effectiveness of the digital implementation for sensorless inductance identification.

North China University of Technology (CN)
Openalex Percentile: Top 76%
Electric Motor Design and Analysis
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Digital Implementation of Switching Model-Based Inductance Identification for IPMSM under Sensorless Control — Fan Zhang · (2025) | TGRS Research Map | TGRS